Multiple geophysical techniques for investigation and monitoring of sobradinho landslide, Brazil

Geophysical methods have a varying degree of potential for detailed characterization of landslides and their dynamics. In this study, the application of four well-established seismic-based geophysical techniques, namely Ambient Noise Interferometry (ANI), Horizontal to Vertical Spectral Ratio (HVSR), Multi-Channel Analysis of Surface Waves (MASW) and Nanoseismic Monitoring (NM), were considered to examine their suitability for landslide characterization and monitoring the effect of seasonal variation on slope mass. Furthermore, other methods such as Ground Penetrating Radar (GPR) and DC Resistivity through Electrical Resistivity Tomography (ERT) were also used for comparison purpose. The advantages and limitations of these multiple techniques were exemplified by a case study conducted on Sobradinho landslide in Brazil. The study revealed that the geophysical characterization of the landslide using traditional techniques (i.e., GPR, ERT and MASW) were successful in (i) the differentiation between landslide debris and other Quaternary deposits, and (ii) the delineation of the landslide sliding surface. However, the innovative seismic based techniques, particularly ambient noise based (HVSR and ANI) and emitted seismic based (NM), were not very effective for the dynamic monitoring of landslide, which might be attributed to the short-time duration of the data acquisition campaigns. The HVSR was also unsuccessful in landslide site characterization i.e., identification of geometry and sliding surface. In particular, there was no clear evidence of the light seasonal variations, which could have been potentially detected from the physical parameters during the (short-time) ambient noise and microseismic acquisition campaigns. Nevertheless, the experienced integration of these geophysical techniques may provide a promising tool for future applicationsThis research was funded by Research of the Federal District Foundation (FAPDF), and The APC was funded by the Department of Geography, University of Brasilia